Quantifying the RNA cap epitranscriptome reveals novel caps in cellular and viral RNA

• Main Authors: Wang, Jin, Chew, Alvin Bing Liang, Lai, Yong, Dong, Hongping, Xu, Luang, Balamkundu, Seetharamsingh, Cai, Maggie Weiling, Cui, Liang, Liu, Chuan Fa, Fu, Xin-Yuan, Lin, Zhenguo, Shi, Pei-Yong, Lu, Timothy K., Luo, Dahai, Jaffrey, Samie R., Dedon, Peter C.
• Other Authors: School of Biological Sciences
• Format: Article
• Language: English
• Published: 2020
• Subjects: Science::Medicine; RNA Characterisation and Manipulation; Mass Spectrometry-based Technique
• Online Access: https://hdl.handle.net/10356/142174
• Institution: Nanyang Technological University

Chemical modification of transcripts with 5' caps occurs in all organisms. Here, we report a systems-level mass spectrometry-based technique, CapQuant, for quantitative analysis of an organism's cap epitranscriptome. The method was piloted with 21 canonical caps-m7GpppN, m7GpppNm, GpppN, GpppNm, and m2,2,7GpppG-and 5 'metabolite' caps-NAD, FAD, UDP-Glc, UDP-GlcNAc, and dpCoA. Applying CapQuant to RNA from purified dengue virus, Escherichia coli, yeast, mouse tissues, and human cells, we discovered new cap structures in humans and mice (FAD, UDP-Glc, UDP-GlcNAc, and m7Gpppm6A), cell- and tissue-specific variations in cap methylation, and high proportions of caps lacking 2'-O-methylation (m7Gpppm6A in mammals, m7GpppA in dengue virus). While substantial Dimroth-induced loss of m1A and m1Am arose with specific RNA processing conditions, human lymphoblast cells showed no detectable m1A or m1Am in caps. CapQuant accurately captured the preference for purine nucleotides at eukaryotic transcription start sites and the correlation between metabolite levels and metabolite caps.